Curiosity is a desktop productivity app for Windows, Mac and Linux.
Finding information can be time-consuming and frustrating: There are just too many files and messages in too many places.
Curiosity gives you one place to search across all your folders and cloud apps like Gmail and Slack. It also searches deep inside files, messages, and attachments. That puts all your information at your fingertips so you can focus and get more done.
Curiosity also works as a launcher so you can open programs, join your next meeting, do math, and more. That means all your work is just a shortcut away.
Curiosity includes industry-grade security features and always keeps your data safe and private on your computer.
Curiosity is good, and constantly updated
Based on our record, Curiosity.ai should be more popular than Apache Lucene. It has been mentiond 13 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I have to find a few examples of relatively small programming libraries that has been rewritten/ported to C++, C# and Java. Example: Lucene (it isn't that small, but still shows what I'm looking for). Source: about 1 year ago
He is talking about impacting the search algorithm. Putting a “+” sounds like it is negatively impacting search quality. Source: over 1 year ago
For example Lucene is a core project common to many search engines, lots of things built ontop of it. And there are similar libraries Https://lucene.apache.org/core/. Source: over 1 year ago
Full-text search Elasticsearch is built on top of Apache Lucene, an open-source information retrieval software. Apache Lucene enables Elasticsearch can perform complex full-text searches using a single or combination of word phrases against its No SQL database. - Source: dev.to / almost 2 years ago
If I had control of the back end I would implement a full-text engine such as Lucene. Generate the lookup table as a batch job and then perform the FTS when the request comes in. If you try to do this real-time, your search will take exponentially longer the larger the data set gets. Source: about 2 years ago
We experimented with it sometime ago for our https://curiosity.ai app, initial training on your data was a bit heavy (at the time, probably fine by today's standards) but nice results if you had enough files. Needs to be done with care as for small datasets as there's not enough info for a model to learn and you end up introducing more noise than anything. - Source: Hacker News / 1 day ago
> I'm in search of a local LLM that can run completely offline for processing personal documents. Key requirements include privacy (no data leaves my machine) and performance (efficient with large datasets). Any recommendations for open-source / commercial solutions that fit the bill in 2024? Also, what's the current state of local LLMs—are: Are they practical and useful, or still facing significant limitations?... - Source: Hacker News / 28 days ago
You can try https://curiosity.ai, supports Windows and macOS. - Source: Hacker News / 2 months ago
We're working on something similar at https://curiosity.ai - no plugins yet but something we have in our roadmap for next year. - Source: Hacker News / 6 months ago
Welcome to the space - I'm one of the founders from https://curiosity.ai! - Source: Hacker News / over 1 year ago
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